Title :
Isolated sign language recognition using hidden Markov models
Author :
Grobel, Kirsti ; Assan, Marcell
Author_Institution :
Lehrstuhl fur Technische Inf., Tech. Hochschule Aachen, Germany
Abstract :
This paper is concerned with the video-based recognition of isolated signs. Concentrating on the manual parameters of sign language, the system aims for the signer dependent recognition of 262 different signs. For hidden Markov modelling a sign is considered a doubly stochastic process, represented by an unobservable state sequence. The observations emitted by the states are regarded as feature vectors, that are extracted from video frames. The system achieves recognition rates up to 94%
Keywords :
feature extraction; hidden Markov models; image recognition; image sequences; doubly stochastic process; feature vectors; hidden Markov models; isolated sign language recognition; signer dependent recognition; unobservable state sequence; video frames; video-based recognition; Arm; Cameras; Computer vision; Data gloves; Deafness; Handicapped aids; Hidden Markov models; Motion analysis; Speech; Stochastic processes;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.625742
